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Systems and signals theory has aided in understanding various kinds of processes such as meteorology, econometrics, engineering, etc. In this work, we explore the applicability of these theories to analyze phenomenon from other terrestrial bodies, specifically the seismic phenomenon on Mars, using data-driven approaches. It is expected that this analysis will provide insights into the formation and interior of the red planet. It will also allow us to draw a preliminary comparison of the seismic phenomenon between the home and red planet. The specific objectives of this work are (i) exploratory analysis of the statistical characteristics and (ii) develop a time-series model using a systematic procedure that was initially developed to analyze Earth data. It involves a rigorous investigation of the specific statistical properties, namely, stationarity, linearity, and Gaussianity, followed by the development of a suitable time-series model that is commensurate with these properties. Our analysis reveals that Mars noise exhibits specific types of non-stationarities, namely, trend and heteroskedasticity. In addition, noise also exhibits linearity and follows a Gaussian distribution. In line with these features, we develop a component model that comprises of a third-order polynomial trend and the Autoregressive Integrated Moving Average - Generalized AR Conditional Heteroskedasticity (ARIMA-GARCH) model. The findings reveal that the specific properties share a striking similarity with home planet data, while the trend appears to be a unique feature. These discoveries, we believe, will pave the way in understanding the red planet. The studies, including model development, are carried out on datasets recorded by the seismometer deployed on Mars during NASA’s Insight mission.

Traditionally, a denoising algorithm is usually applied to enhance useful reflection seismic signals, or to increase the quality of the waveforms recorded in the seismic data. The strong noise left in the filtered data after denoising is a long standing drawback of many state-of-the-art denoising algorithms. In addition to removing noise, we are proposing a new way to detect the waveforms, which can also enhance the useful signals. We propose a waveform classification algorithm based on a clustering method, e.g., to classify a data point in the data into signal or noise. The waveform classification algorithm can be applied directly to the noisy data to solely output the picked signals and thus can be a complete substitute to a traditional denoising algorithm. A better way for “denoising” is to pick the signals from a traditional denoising algorithm with the labels classified from the noisy data. At the same time, we also propose a novel automatic denoising method based on the empirical wavelet transform (EWT). We use the EWT method as a template to show how the proposed waveform classification method can be combined with a traditional denoising algorithm to output a superb denoised signal.

This paper presents a structural assessment project for a construction training center in Hong Kong. The training center consists of coupled main and complementary buildings. Due to the vigorous activities in the training center, the objectives of the project include conducting operational modal analysis (OMA) of the buildings to assess their structural performance and the coupling of vibrations between the two buildings. OMA is conducted using Bayes-Mode-ID recently developed by the authors, which is an efficient Bayesian modal-component-sampling system identification method for field testing of civil engineering structures under ambient vibrations. Implementation issues for Bayes-Mode-ID are discussed in detail for the full-scale coupled structural system. Due to the large number of measurement points (high resolution mode shapes are desired for understanding the coupling behavior of the system) and limited number of sensors, the measurements were divided into 21 setups in order to properly characterize the dynamics of the building. Each setup covered one portion of the training center and the partial mode shapes from different setups were assembled to provide the global mode shapes. By following a Bayesian approach, not only the most probable values (MPVs) of the modal parameters (modal frequencies, modal damping ratios and mode shapes) but also their associated uncertainties can be obtained. The identified modal parameters reveal interesting dynamic behaviors of the coupled-building and they will be helpful for structural assessment and structural health monitoring (SHM) of the training center in the future.

The link between hurricanes or typhoons and their generated ambient noise has recently become a frontier topic in the field of applied seismology. In the Mediterranean region, infrequent tropical-like cyclones, known as Medicanes or Mediterranean hurricanes, with similar characteristics with hurricanes appear, with the most recent storm occurred on September 27–30, 2018 in South Greece, which characterized by gale winds, severe precipitation, and a low pressure center, accompanied with a spiral pattern of thunderstorms. In this work, we describe the Medicane’s induced ambient seismic noise fluctuations, as recorded in seismological station along to the path of the recent Medicane, in terms of non-extensive statistical physics. We found that the Medicane’s induced ambient seismic noise increments follow the q-Gaussian distribution. This indicates that Medicane induced ambient seismic noise’s fluctuations are not random and present long-term memory effects that could be described in terms of Tsallis entropy. Our results suggest that in the Medicane system that affected the Southwest Peloponnese the q –values of the induced ambient seismic noise’s fluctuations in the Kalamata (KLMT) seismological station located in Southwest Peloponnese are q ≈ 1 . 67 , which corresponds to n=2 degrees of freedom system, indicating that Medicane induced ambient seismic noise fluctuations compose of two independent Gaussian random variables. For stations as that of APE (Apiranthos, Naxos island, Cyclades), where an attenuated Medicane was observed, a q ≈ 1.57 obtained, which is similar with that observed in the KNDR (Koundoura, South West Crete) seismological station, where the Medicane appears before its main organization as intensively observed in the KLMT station. For the CHAN (Chania, West Crete ) station a q ≈ 1.32 was observed which corresponds to about 5 degrees of freedom indicating that Medicane induced ambient seismic noise fluctuations compose of about five independent Gaussian random variables, in agreement with the week intensity of Medicane observed in Chania.

Wave barriers have been commonly used to reduce impact of ambient vibrations. In this paper, inspired by the concept of the invisibility cloak and Fermat’s principle, a new type of wave barrier, named as wave guided barrier, is proposed to effectively isolate areas of interest (e.g., buildings) from vibrations due to antiplane elastic waves. This new wave guided barrier is made of anisotropic metamaterial with layered structure and can guide the elastic waves to propagate along specific direction. Wave propagation characteristics of anisotropic metamaterial are first derived. Then, a specific wave guided barrier is designed. The designed wave guided barrier only uses two materials commonly used in practical engineering. Numerical results from both frequency domain and time domain analyses showed that the wave guided barrier can effectively isolate antiplane elastic waves.

Seismic interferometry based on ambient seismic noise was used to image the 3D S-wave velocity field of a subsurface disturbed by mining under the geological conditions at the KGHM Rudna copper mine in southwestern Poland. We recorded ambient seismic noise data for 3 months using 11 surface-mounted broadband seismometers located across the mining area. We used ambient-noise cross-correlation techniques to create a three-dimensional S-wave velocity model of the Cenozoic and Triassic formations up to a depth of 500 m. Cross-correlation functions (CCFs) indicate the Rayleigh and Love waves; however, only the Love waves in the 0.19–0.4 Hz frequency range were reliable, based on the symmetry of the CCFs in the positive and negative conditions. Imaging using the Love waves indicated that the changes in the S-wave velocity field in the model may be explained by the subsidence processes occurring above the mined area. The S-wave velocity decreased above the areas of the current mining operations. However, the S-wave velocity increased above older mined areas, probably due to suppression of the subsidence process and progressive consolidation of the geological medium over time. We also observed low-velocity anomalies in the intersection zones of the larger faults, with high energy seismic events. This could be caused by fault activation by current mining operations and a reduction in the stiffness of the layers in the fault intersection zone. This study presents the possibility of imaging the subsurface layers in a mining area using ambient seismic noise. It also has the potential to give a broader insight into how a geological medium responds to mining in terms of protecting the terrain surface and developing mining technologies.

Seismic noise suppression is an important step in the seismic imaging community. We propose a variational mode decomposition (VMD) based method to attenuate spatially incoherent random noise. The VMD method has a solid theoretical foundation of mathematics and high calculation efficiency. Besides, compared with the recursive mode decomposition algorithms, e.g., the EMD and EEMD methods, it has advantages in solving the mode mixing problem and more powerful anti-noise performance. The VMD method can adaptively decompose a seismic signal into several intrinsic mode functions (IMF). Removing the highly oscillating IMF components can suppress the high frequency/wavenumber noise. However, the VMD algorithm has a drawback that the mode number needs to be set artificially before decomposition. The mode number is difficult to estimate when a signal is a complex nonlinear and non-stationary one. Thus, the signal is still coupled in low frequency/wavenumber noise. Thereupon, the singular spectrum analysis (SSA) algorithm is applied to filter the low-frequency/wavenumber noise. In this paper, a simulated seismic dataset and a real seismic dataset are analyzed by the proposed algorithm. The results indicate that the proposed algorithm is robust to noise and has high de-noising precision.

Structural health monitoring is required to interpret damaged structures in terms of locations and severity, even remaining performance of the damaged members. Therefore, this study proposes a new artificial intelligence-based structural health monitoring strategy based on neural network modeling. A neural network model is developed in accordance with a numerical model which is derived from the identified modal properties under ambient vibrations. The stochastic subspace system identification is first implemented to derive the natural frequencies and mode shapes of a healthy structure. These natural frequencies and mode shapes are then employed to derive a simplified model of this structure, allowing changing stiffness terms to construct various damage patterns. A neural network model is trained and built by the modal properties of the structure with these damage patterns. After a critical event occurs (e.g., earthquakes), this neural network model can be employed to estimate the damage patterns in terms of stiffness reduction. In this study, a numerical example consisting of two damage scenarios is carried out. This example studies a seven-story building with a single and multiple damaged columns in order to evaluate performance of the proposed structural health monitoring strategy. Moreover, the proposed structural health monitoring strategy is also applied to an experimental test of a scaled twin-tower building with weak braces in some floors. Partially modal properties of the structure are obtained from the stochastic subspace system identification, while a simplified model is developed in accordance to the identified modal properties of the healthy building. Then, a neural network model is established based on this simplified model. After seismic events, this neural network model is employed to carry damage detection of this building in terms of damage locations and levels. As a result, the proposed artificial intelligence-based structural health monitoring strategy is quite effective to locate damage if the identified modal properties are relatively accurate.

To characterize the subsurface geomechanical response to hydraulic fracturing (HF) activities, we study the spatiotemporal changes of seismic velocity during the completion of four HF wells in the Fox Creek area, Alberta, Canada. We estimate temporal velocity changes (dv/v) from ambient seismic noise recorded during the Tony Creek Dual Microseismic Experiment (ToC2ME) by comparing a 5-day stacked noise correlation function with a reference noise correlation function stacked over the deployment period. In the frequency band (0.1–0.4 Hz) most sensitive to the injection depths (~3.4 km), we observe daily dv/v that revealed alternating gradual velocity decreases and increases with magnitudes in the range of ±0.9%. We found a strong temporal correlation between the onset of velocity decreases and periods of intense seismicity, suggesting that the observed dv/v reductions are likely caused by stress-induced subsurface deformation due to elevated pore pressures, increased crack density, and ground shaking. A period of dv/v increase observed between the beginning and end of different well stimulation is attributed to crustal healing. Comparing the dv/v time series with injection parameters, we observed a 272.66% increase in induced seismicity and 50% more reduction in dv/v during the second injection phase that are correlated with 90.53%, 169.64%, and 4.34% increase in the injection volume, rate, and pressure, respectively. Our study provides valuable new information on the changes in reservoir elastic properties within the Western Canadian Sedimentary Basin. It also demonstrates that coda wave interferometry using data from dense seismic arrays near injection sites can be an additional tool for monitoring hydraulic fracturing operations.

Tensegrity structures are cable-strut systems held in equilibrium due to self-stress. There is potential for damage tolerance when they are kinematically redundant. In this paper, detection and location of a ruptured cable in a deployable tensegrity footbridge are studied through monitoring changes in dynamic behavior. Position values and axial load values of elements are measured before, during, and after a cable breakage. Free and forced-vibration-induced dynamic behavior of the tensegrity structure are characterized in the state of deployment (one half of the structure) and in-service (full structure). Examination of ambient vibrations for the half structure and forced vibrations for the full structure successfully led to detection of ruptured cables. Exclusion of possible damage cases for location using measurements effectively reduces the number of candidate cases when using nodal displacement measurements. Correlation methods using strain measurements are also successful to locate a ruptured cable. These methods reveal the potential for self-diagnosis of complex sensed structures.

The distribution and the interconnection of magmatic bodies beneath volcanic arcs is key to asses volcanic hazard and eruptive processes taking place at convergent margins. We use ambient seismic noise Rayleigh-wave tomography to investigate the three-dimensional shear-wave crustal velocity structure of the Southern Central Andes between latitudes 33°S and 38°S (for the upper 30 km). We investigate the occurrence of magmatic reservoirs in the upper crust and show how their geometry is affected by local tectonics. The first prominent feature to be observed is the shear-wave velocity contrast between the volcanic arc and the faster fore-arc region. We further identify areas of low shear-wave velocity from 3 km to 10 km depth beneath the volcanic arc, striking N-S, that we interpret as zones of fluid-rich crust, possibly characterised by confined regions of partial melts. Our results allow us to derive a model for the crustal structure of the Southern Central Andes. We propose that partial melts, marked by lower shear-wave velocity anomalies, are connected to shallower structural levels and reservoirs by brittle regions where dikes and exsolved fluids may propagate.

Natural hazards result in ill-conditioned structures with unfavorable damage. To early recognize damage existence, structures can be screened by damage detection methods after a critical hazard event. These damage detection methods are often developed based on a centralized acquiring and computing system that challenges the feasibility of deployment in a large-scale structure. Decentralized damage detection methods alter a single system to multiple subsystems that allow spatially distributing in a structure and yield comparable performance with the centralized approach. In this study, a decentralized damage detection method based on modal prediction errors via multiple banks of Kalman estimators is proposed. First, a sensor network is comprised of multiple subsystems over a structure of which the subsystems have overlapped sensing nodes. These subsystems are individually identified by an input–output frequency-domain system identification method under ambient vibrations. The identified models are then converted into several banks of Kalman estimators, and the estimators generate the estimation of structural modal responses. The prediction errors are calculated from the differentiation between measured and estimated modal responses, and the accumulated standard deviations of modal prediction errors serve as the damage indices for recognizing the damage occurrence, locations, and levels. A numerical example is introduced to demonstrate the proposed method as well as to evaluate the detection effectiveness. Moreover, the proposed method is also experimentally verified by a scaled twin-tower building using shake table testing. The experimental results indicate that the proposed method is quite effective to inform damage of structures in terms of damage occurrence, locations, and levels.

Detection, forecasting, early warning, and effective monitoring are key aspects for the delimitation of sinkhole-prone areas and for susceptibility assessment and risk mitigation. To attain these goals, direct and indirect techniques can be employed, and the integration of different indirect/non-invasive geophysical methods including 2D- and 3D-electrical resistivity tomography, microgravity, and single-station seismic noise measures was carried out at “Il Piano” (Elba Island – Italy), where at least nine sinkholes occurred between 2008 and 2014. The most likely origin for these sinkholes had been considered related to net erosion of sediment from the alluvium, caused by downward water circulation between the aquifer hosted in the upper layer (Quaternary alluvial deposits) and that in the lower (Triassic brecciated dolomitic limestone and Cretaceous slate). The integrated geophysical survey, therefore, was carried out a) to differentiate shallower from deeper geological layers, b) to detect possible cavities that could evolve into sinkholes, c) to suggest possible triggers, and d) to delimit the sinkhole-prone area. The results of the integrated geophysical surveys suggest that the study area is mainly characterised by paleochannels, and that the sinkhole-prone area boundaries correspond to these paleochannels.

Subsurface geometry, particularly the depth of bedrock, is crucial in seismic hazard studies because the basin geometry has been shown to play an important role in the altering of seismic waves. Estimating the bedrock surface using ambient seismic noise analysis has been undertaken by many researchers, with most studies focusing on sites with a strong impedance contrast between the bedrock and the overlying materials. The application of this technique at regolith sites, which is subjected to impedance contrasts in the low to high range is underdeveloped and requires further attention. This study seeks to address this need and is focused on the city of Adelaide in South Australia, which exhibits site amplification and is associated with various impedance contrasts. Analyses of ambient noise data are carried out using the generic function (GF) of the classic horizontal vertical spectral ratio (HVSR) method and the spatial autocorrelation (SPAC) technique to estimate the depth to bedrock. Comparison of the bedrock depth predictions from the seismic methods with boreholes drilled in close proximity to the measured sites demonstrate that the SPAC method provides superior estimates especially to those obtained from the other approach. This work demonstrates that the microtremor SPAC method is an effective tool for estimating bedrock structure at regolith sites.

The damping ratio and the resonance frequency represent relevant health indicators in structural health monitoring, and they are key parameters in the design of buildings. The combination of two modal parameters (i.e., damping, frequency) is reported to vary in time due to changes in environmental conditions, and with damage to the structure and dynamic loading. Amplitude dependence of the damping and frequency parameters has also been reported for strong loading, such as strong winds. However, none of these reasons can explain the much higher fluctuations of the damping values compared to the resonance frequency in the amplitude range of natural ambient vibrations. The objective here is to investigate if any amplitude dependence in this lower range of loading can explain the observed differences in the scattering of these two modal parameters. To do so, the first approach consists of a study of vertical clamp-free beams made out of different materials. Secondly, the observations and interpretations obtained are scaled up to buildings under continuous monitoring. Finally, we consider the fluctuation–dissipation theorem to explain these uncommon results.

This paper investigates and compares the performances of two simulation models to predict the footbridge response to vertical pedestrian dynamic actions. For this purpose, a rational procedure based on experimental tests, identification, model-updating and simulation is addressed. The object of study is the Pasternak footbridge, a curved cable-stayed footbridge prone to human-induced vibrations. The footbridge dynamic behaviour is investigated thanks to an experimental campaign. Accelerations due to ambient vibrations are recorded and the modal parameters of the structure are identified. The dynamic response to pedestrian actions is investigated performing several experimental tests with different-sized groups of pedestrians. To simulate the dynamic response to pedestrian actions, a Finite Element (FE) model of the footbridge is developed and calibrated so that the numerical dynamic properties match the experimental ones. The structural response to human loads is evaluated through two advanced simulation methods. The first one is based on a periodic walking force and is employed to perform dynamic analyses with the FE model. In the second one, a multi-harmonic force model, which considers the variability of the walking force, is adopted and the dynamic response is evaluated via modal decomposition. Finally, numerical and experimental results are compared with each other.

In this work we study in terms of Tsallis statistical mechanics the properties of microtremors’ fluctuations in two church bell towers, which are monuments of cultural heritage, in the city of Chania (Crete, Greece). We have shown that fluctuations of ambient vibrations recordings in the Church tower bells follow a q -Gaussian distribution. The behavior of Tsallis q parameter with the level (high) of the measuring point within the tower and the amplification factors at that points as extracted from horizontal-to-vertical (HVSR) spectral ratios are presented and discussed. Since q decreases as the amplification factor increases, we could suggest q as a vulnerability index, where, as q decreases approaching unity, then the structural system is getting more vulnerable. The latter approach suggests that introducing ideas of Tsallis statistics could be useful in characterizing extremely complex processes as that governed the estimation of seismic vulnerability in which a multidisciplinary approach is required.

Unexpected geological structures can cause safety and economic risks during underground excavation. Therefore, predicting possible geological threats while drilling a tunnel is important for operational safety and for preventing expensive standstills. Subsurface information for tunneling is provided by exploratory wells and by surface geological and geophysical investigations, which are limited by location and resolution, respectively. For detailed information about the structures ahead of the tunnel face, geophysical methods are applied during the tunnel-drilling activity. We present a method inspired by seismic interferometry and ambient-noise correlation that can be used for detecting scatterers, such as boulders and cavities, ahead of a tunnel while drilling. A similar method has been proposed for active-source seismic data and validated using laboratory and field data. Here, we propose to utilize the seismic noise generated by a Tunnel Boring Machine (TBM), and recorded at the surface. We explain our method at the hand of data from finite-difference modelling of noise-source wave propagation in a medium where scatterers are present. Using the modelled noise records, we apply cross-correlation to obtain correlation gathers. After isolating the scattered arrivals in these gathers, we cross-correlate again and invert for the correlated traveltime to locate scatterers. We show the potential of the method for locating the scatterers while drilling using noise records due to TBM.

This study shows a formulation that allows obtaining theoretical results that show the energy contents associated with the propagation of compressional and shear seismic waves (P- and S-waves respectively) for the case of a two-dimensional medium. During the propagation of seismic waves, the energy contents of P- and S-waves show fixed proportions according to the properties of the medium where they propagate (i.e. density, wave propagation velocity and Poisson ratio). Theoretically, a material with a Poisson ratio of 0.35 implies that P-waves will only represent 18.75% of the total energy while the other 81.25% will be contributed by S-waves. For a Poisson ratio of 0.45, S-waves will be enormously powerful and contribute with 91.67% of the total energy during propagation. On the other hand, it is also possible to obtain the energy contents through correlations of seismic motions by means of the interpretation of recovered seismograms. In this study, it is also shown that under certain conditions, the recovered energy converges to exact solutions. Our results are validated using published solutions showing an excellent agreement. In addition, theoretical examples have been developed simulating seismic noise and it has been found that energy contents of the P- and S-waves are also satisfied.

The spectrum of ambient seismic noise shows strong signals associated with tropical cyclones, yet a detailed understanding of these signals and the relationship between them and the storms is currently lacking. Through the analysis of more than a decade of seismic data recorded at several stations located in and adjacent to the northwest Pacific Ocean, here we show that there is a persistent and frequency-dependent signature of tropical cyclones in ambient seismic noise that depends on characteristics of the storm and on the detailed location of the station relative to the storm. An adaptive statistical model shows that the spectral amplitude of ambient seismic noise, and notably of the short-period secondary microseisms, has a strong relationship with tropical cyclone intensity and can be employed to extract information on the tropical cyclones.

Sound is used by a variety of marine taxa for feeding, reproduction, navigation and predator avoidance and therefore alterations to the soundscape from industrial noise have the potential to negatively affect an animal’s fitness. Furthermore, responses to industrial noise would also have the potential to negatively influence commercial fishing interests. Unfortunately marine invertebrates are generally underrepresented in the seismic effects literature. Snow crab harvesters in Atlantic Canada contend that seismic noise from widespread hydrocarbon exploration has strong negative effects on catch rates. We repeated a Before-After-Control-Impact study over two years to assess the effects of industry scale seismic exposure on catch rates of snow crab along the continental slope of the Grand Banks of Newfoundland. Our results did not support the contention that seismic activity negatively affects catch rates in shorter term (i.e. within days) or longer time frames (weeks). However, significant differences in catches were observed across study areas and years. While the inherent variability of the CPUE data limited the statistical power of this study, our results do suggest that if seismic effects on snow crab harvests do exist, they are smaller than changes related to natural spatial and temporal variation.

The use of artificial periodic structures such as periodic wave barriers and seismic metamaterials has attracted attention as an effective approach to reduce the impact of ambient vibrations or earthquakes. In previous research, a large amount of steel was usually used in the design of seismic metamaterials to achieve ultra-low surface wave band gaps (BGs). However, the use of such large amounts of steel is inconvenient and expensive in practical engineering applications. To address this issue, this study considered the use of common building materials, namely, concrete, rubber, and soil, for the preparation of seismic metamaterials. Using these three materials, a one-dimensional (1D) seismic metamaterial composed of periodic in-filled pipes and a substrate was proposed. Ultra-low surface wave BGs (0–10 Hz) of the seismic metamaterial were identified using the sound cone method. Several important geometrical and material parameters that could influence the BGs were studied. Based on the 1D metamaterial, a 2D seismic metamaterial with a complete ultra-low BG was proposed to filter Rayleigh waves at any angle in the surface plane. The screening effectiveness of the 1D and 2D seismic metamaterials was evaluated using 2D and 3D numerical models, respectively. The results show that the ultra-low BG width decreases with an increase in the distance between two adjacent in-filled pipes. The small height of the in-filled pipe is beneficial for achieving a large ultra-low BG. A high elastic modulus and a low mass density of the soft filling material correspond to a large ultra-low BG width. The generation of ultra-low BGs in both 1D and 2D seismic metamaterials is attributed to the torsional resonance of the filling soft material. This study can serve as a reference for the design of new seismic metamaterials with practical value in engineering.

Seismic stations are usually used to record seismic event and, therefore, they are recommended to be installed far from railways and traffic roads in order to avoid the superposition of ambient noise signals to those provoked by an earthquake. In this paper, instead, seismic stations, placed intentionally in areas near railway and traffic roads, are used to characterize the subsoil spectral properties and to assess the effect of vibrations due to trains and vehicles. A cemetery in the green countryside near Florence is chosen as a reference case study to deal with this topic. Most of the buildings in the cemetery area are affected by an extensive crack pattern. In January 2020 five seismic stations were installed in order to evaluate if the trains running in the tunnels of the regional and high-speed railway lines located below and in the vicinity of the cemetery and the vehicles traveling on the nearby A1 highway and regional road can produce vibrations in the ground that justify the observed damage pattern. Collected data are analyzed using the Nakamura technique in order to estimate the dynamic properties of the ground and compared to the limits provided by the current regulations. Furthermore, the trend of the Root Mean Square average over the entire recording period is computed as well. From the obtained results, it is possible to highlight that the average daily oscillation level increases from early morning until 7 p.m. and then it decreases, and also that the highest amplitudes of transients are concentrated in the late evening and during the night, when the background noise is lower. Furthermore, the computed values of the maximum and average amplitudes are lower than those that can cause damage to buildings as defined by the guidelines, the eigenfrequency of the ground falls in a range far from that ascribable to the cemetery buildings, so that the resonance effects can be excluded. In order to confirm these results, the amplitude of ground shaking due to recorded transients is compared to that produced by two earthquakes (a 3.4 Mw local earthquake at more than 100 km and a Mw 6.6 teleseism from Turkey) which occurred during the monitoring period. One can conclude that it seems unlikely that the shaking produced by nearby vehicles and trains could be responsible for the observed damage.

Rejecting noise in seismic data while not affecting the amplitude of useful signals is a long standing problem in seismic data processing. Seismic noise attenuation can be formulated as a nuclear norm minimization (NNM) problem. To meet the assumption that seismic data should have low nuclear norm, we first map the seismic data into a low-rank matrix based on a trace prediction strategy. We provide detailed algorithm workflow and mathematical analysis of the trace prediction method. The seismic data after trace rearrangement is demonstrated to be locally low-rank. The NNM problem is then solved via the singular value thresholding (SVT) algorithm. The effectiveness of the proposed method is validated via both synthetic and field data examples. We also test the robustness of the proposed method with respect to random noise, spiky noise, and blending interference. Compared with the state-of-the-art predictive filtering method, median filtering method, singular spectrum analysis method, and curvelet thresholding method, the proposed method obtains an obviously better performance in compromising signal preservation and noise removal.

Non-Orthogonal Combined Fourier Analysis of the Smoothed Signals (NOCFASS) helps to extract the reduced/invariant spectrum from the total Fourier-spectrum that contains a small number of frequencies with the linear dispersion law Ωk = a⋅k + b. The paper presents a new technique to treat original data of natural processes like seismic ambient noise, measured by the seismic gradient system with geophones on the surface. The authors show an example of the signal processing (July 14th-16th 2018) in the Ukok-2 point located in Tien Shan. A wide set of signals with a trend that is obtained from the set of initial trendless sequences (TLS) by means of integration procedure. This selected spectrum with eliminated high-frequency components is considered as an invariant spectrum, which contains only the basic low-frequency modes. The results are useful for the further detection of different random factors that disturb the TLS behavior.

The Hengill volcanic system is located in the Reykjanes Peninsula (Iceland) and hosts two large geothermal power plants: Nesjavellir and Hellisheiði. This area is the next target for the Iceland Deep Drilling Project (IDDP) to search for super-critical fluids. Here, we investigate the potential for ambient seismic noise tomography to be used as a geothermal exploration tool. The results are compared with different geophysical observables, of which resistivity modeling shows an excellent correlation with our results. We also observe a prominent seismic velocity reduction to the south of Hverahlið, where the most powerful boreholes in the region are located.

Concrete gravity dams are critical infrastructures for communities to meet the basic human needs as well as rising standards of living. Most of the existing concrete gravity dams in Italy were built before the introduction of seismic regulations. Although no concrete gravity dams have as yet suffered a catastrophic collapse during or after a seismic event, their preservation remains a key aspect for communities, also in view of that older dams may have deteriorated to a critical level. For these reasons, researchers and practitioners in dam engineering are working to improve seismic fragility, and ultimately seismic risk, assessment procedures. Since no case histories are available, numerical modelling plays an important role, even though many uncertainties can affect the models and then the estimation of the seismic fragility. This paper presents a robust hierarchical Bayesian framework for the calibration of dynamic parameters of dam numerical models based on ambient vibrations, which allows an analyst to reduce uncertainties in the seismic fragility derivation. A probabilistic predictive model of the dam modal behaviour based on the general Polynomial Chaos Expansion is adopted in order to reduce the computational burden and a numerical algorithm for the solution of the inverse problem based on Markov Chain Monte Carlo is also presented. The proposed approach is applied to an existing large concrete gravity dam in Italy, and the effect of epistemic uncertainty reduction is finally evaluated in terms of fragility curves.

One of the key and difficult points in seismic data processing is seismic data denoising. Under the influence of the acquisition environment, the collected seismic data usually have low signal-to-noise ratio (SNR) and low resolution. In desert region of western China, different from other regions, the random noise there has complex characteristics of non-Gaussian, non-stationary and non-linearity. Its main frequency is quite low and its spectral overlap with those of effective signals. Moreover, large amount of data and intelligent requirements make traditional denoising methods encounter difficulties. In addition, the existing deep learning denoising methods also reveal two problems: first, they can only effectively suppress simple seismic noise such as Gaussian noise. But for the case of desert noise, they usually mistakenly judge noise as effective signals and destroy signal characteristic structure. Second, what is more important, in supervised-based methods paired noisy and pure data are usually used as training set. However, there is no noise-free data in actual desert seismic data, which severely limits the processing performance of supervised-based networks. Thus, a new parameter-shared variational auto-encoding adversarial network (PS-VAAN) is proposed for desert seismic data denoising in this paper. This new method includes two encoders, two generators and two discriminators . It can realize domain conversion from noisy data domain to pure data domain. We construct relatively complete unpaired pure and noisy data training sets for training, and design reconstruction loss function and adversarial loss function to optimize network parameters. Moreover, cycle-consistency loss is introduced to make sure two domains mapping into the same space. Compared with the state-of-art denoising methods on synthetic and actual seismic records, the proposed method not only has superior denoising ability, but also has strong feature extraction and fitting ability to recover effective signals with almost no energy loss .

The method of Proper Orthogonal Decomposition (POD) is one of the popular techniques used in structural dynamics. Unlike Linear Natural Modes (LNMs), Proper Orthogonal Modes (POMs) derived from the POD method, depend on the excitation loads in addition to the mass and stiffness of the dynamical system. According to the various researches in establishing a general connection between POMs and their respective LNMs, it has been found that except in some special cases, the natural system mode shapes cannot be extracted from the POMs. Despite efforts to find the general relation between POMs and LNMs, the use of POMs in the determination of natural frequencies and damping ratios has received less attention. This paper aims to use the POMs as a modal analysis tool to extract the natural frequencies and damping ratios of linear dynamical systems from their experimental vibrational responses. For this purpose, a POD-based algorithm is proposed to achieve this objective. In the mentioned methodology, at first, the equation of motion of a MDOF system is decomposed into several SDOF equations using proper orthogonal modes. Then the responses of the SDOF models are calculated in proper modal coordinates. Finally, the Power Spectrum Density (PSD) and the Auto Correlation Function (ACF) of their responses are used to determine the natural frequencies and damping ratios, respectively. The accuracy and precision of the results are evaluated by numerical and experimental validation. Two different conventional loading states, including impulse loads and ambient vibrations, are studied. Good agreement was observed between the POD-based results and those obtained from the FE and two other conventional operational modal analysis (OMA) methods. Also, it was found that in the modal identification process by POD-based algorithm, the noise effects are transmitted to the latest proper modes, so in noisy conditions, the accuracy of the modal characteristics corresponding to the primary natural modes will not be affected. Some other findings of this research will be presented at the end of the article.

SMAV (Seismic Model from Ambient Vibrations) is a mathematical model for predicting the seismic response of an existing building subjected to earthquake that produces no severe damage. The model is based on the identification of the building experimental modal parameters from ambient vibration together with few information about its geometry and constructive typology. The dynamic response of the structure is obtained by a modal superposition where all the inertial properties are concentrated in the center of gravity of the floors or floor sections. The non-linear behavior, which typically occurs during even nondestructive earthquakes, is considered by assigning appropriate laws of variation to the natural frequencies as the deformation increases. This paper presents the development of SMAV to reinforced concrete frame buildings with infill walls and the application to real cases. Specific Frequency Shift Curves (FSCs), that relates the vibration amplitude to the variations of the natural frequencies, have been developed. Such FSCs are a fundamental feature of SMAV, because they allow the seismic nonlinear behavior to be simulated through an equivalent iterative linear analysis. Therefore, in order to comply with the declared aim, in this work the attention is focused on the definition of a suitable simplified model for the generation of FSCs, valid for reinforced concrete frame buildings with infill walls. In the adopted model the global behavior of the infilled frame is simulated by considering the two components of the system, i.e the bare frame and the infill masonry panel, as working in parallel. The mutual interaction between them is modeled by suitably modifying the collapsing mechanism of the masonry panel. The stochastic approach for modeling the seismic response of infilled RC buildings, considering different kinds of infills and taking account of the nonlinearity which arises during a seismic event, is illustrated in detail. The validation of the FSCs has been performed by using the experimental seismic response of buildings as recorded by permanent accelerometric monitoring systems. Finally, two case studies related to the seismic response recorded on a regular and an irregular building, respectively, are presented by comparing the computed end experimental seismic dynamic responses, in order to prove the SMAV ability in reproducing the behavior of RC infilled frame buildings subjected to nondestructive earthquakes.

A shear-wave velocity model of subglacial Katla volcano, southern Iceland, has been developed using ambient seismic noise tomography based on data from a temporary network operating between May 2011 and August 2013 and permanent stations around the volcano. Phase-velocity dispersion curves were obtained using cross-correlations of vertical components of 136 station pairs and non-linearly inverted for phase-velocity maps between 1.7 and 7.5 s. Local dispersion curves were inverted for shear-velocity variation with depth using a grid search imposing a fixed ice layer at the top. The resulting one-dimensional (1-D) velocity models were combined to obtain a pseudo three-dimensional (3-D) model with estimated lateral resolution of 8 km and depth resolution varying from close to 1 km near the surface to about 8 km at 10 km depth. Shear wave velocities are generally higher within the Katla central volcano than in its surroundings. The most striking feature of the model is a high-velocity anomaly beneath the caldera at > 6 km depth interpreted to be due to cumulates resulting from differentiation of shallower magma intrusions and remelting of subsiding upper crust. No shallow low-velocity anomaly is resolved beneath the central caldera, but a low-velocity region is found at 2–4 km depth beneath the western half of the caldera. V P /V S ratios, estimated from average velocity-depth profiles from surface-wave data and higher frequency P-wave data, are anomalously high (> 1.9) compared to average Icelandic crust, particularly in the top 2–3 km. This is argued not to be an artifact due to lateral refraction or topography. Instead, this anomaly could be explained as an artifact caused by velocity dispersion due to attenuation and a difference in frequency content, and possibly to a degree by the compositional difference between the transalkalic Fe-Ti basalts of Katla and average tholeiitic Icelandic crust.

The weighted nuclear norm minimization method as an extension of nuclear-norm minimization was applied to image denoising originally. It is a kind of low rank matrix approximation method that can estimate the noiseless matrix from its noise version. The effective structures of image have a certain degree of repeatability and the weighted nuclear norm minimization method just utilizes this property to construct an approximate low rank matrix. Taking into account the spatial characteristics of seismic data and the redundancies of valid information, we propose to adopt the weighted nuclear norm minimization method to suppress seismic random noise. In this method the block matching algorithm is helpful for the recovery of seismic events because the texture blocks sharing the same reflection events are the most similar. Even when the signal to noise ratio is − 10 dB, this novel method still be able to clearly recover signals. Experiments on both synthetic and real seismic data show that the weighted nuclear norm minimization method can not only suppress the random noise but also better preserves the valid information of seismic signal when compared to the common seismic denoising methods such as the Wavelet and Time Frequency Peak Filter.

The challenges of accurately identifying the dynamic characteristics of bridge structures from ambient vibration responses persist because, unlike in the ideal laboratory environment, elevated levels of noise in data are unavoidable at any in-situ testing site and may have detrimental effects on the modal parameter identification process and results. This is especially true for vibration tests conducted under weak ambient excitation sources resulting in poorer signal-to-noise ratios (SNRs). This paper presents an investigation into the feasibility and reliability of modal identification using operational modal analysis (OMA) techniques under such weak excitation circumstances and with responses measured by inexpensive stand-alone accelerometers/data recorders. An eleven-span concrete motorway off-ramp bridge, closed to traffic, was excited only by ground vibrations generated by traffic on the motorway passing underneath the bridge as well as on nearby motorway on- and off-ramps, weak winds, and possible micro tremors. A high spatial resolution of measuring points on the bridge deck was used to collect vibration responses. Three output-only modal parameter identification algorithms were utilised to extract the modal properties, namely the peak picking (PP), the frequency domain decomposition (FDD) and the data driven stochastic subspace identification (SSI) method. Nine lateral and three vertical modal frequencies below 10 Hz could be identified despite the weakness of the environmental excitations and noise in sensors. The identified experimental natural frequencies were stable, damping ratios, however, had a marked scatter. A comparison with the results of a numerical modal analysis using a finite element model revealed, however, that several higher order vertical modes were missing from the experimental results altogether, and some of the OMA methods missed the fundamental lateral mode. Overall the PP method was the most successful in finding the largest number of frequencies but the SSI method yielded the highest quality mode shapes. The SSI method is, however, computationally more expensive that the remaining two methods. For quick, preliminary results, the PP and FDD methods can still be useful and detailed analyses could use SSI and FDD. Overall, the study argues that output-only system identification can provide useful quantitative insights into the modal properties of stiff bridges even under weak environmental excitations, or poorer SNRs, but its limitations need to be acknowledged.

A MW6.0 earthquake struck the Central Italian Apennines on August 24th 2016, followed by an important seismic sequence characterized by hundreds of aftershocks . The earthquake caused fatalities and partially destroyed several towns surrounding the epicentral area. In this context the Italian Centre for Seismic Microzonation and its applications was involved for the seismic characterization of the struck area. Using ambient vibrations spectral ratios at seventy-five sites and shear wave velocity profiles obtained through surface waves dispersion properties we assessed seismic site response properties in the Pretare and Piedilama villages located in the territory of Arquata del Tronto. The survey performed inside the valley in which the two villages are located set into evidence that the spectral ratios often show a predominant frequency ranging between 3.0 and 5.0 Hz or several peaks that can be related to some alternating layers with different velocities. Conversely, along the valley flanks, where the geological substratum outcrop, spectral ratios tend towards low amplitude values. The soft sediments inside the valley are characterized by shear wave velocity lower than 350 m/s, whereas the geological substratum has shear wave velocity ranging between 600 and 1200 m/s. The integrated interpretation of both geophysical and geological data, made possible to infer subsoil models of the investigated areas identifying the depth of the seismic bedrock and characterizing the buried morphology.

There is promise in the use of bistable devices to transduce ambient vibrations into electrical power. However, it is critical to sustain the relatively large amplitude snap-through motion, or interwell motion, to significantly improve the responsiveness of bistable devices as compared to linear resonance-based approaches. This work posits that relatively stiff structural elements can be placed in the vicinity of the equilibria of bistable devices such that the discontinuous change in dynamics will tend to eject an otherwise small amplitude motion into the large amplitude interwell orbit that is to be preferred for energy harvesting applications. The discontinuous nonlinear dynamic equations of motion are derived and a proxy system parametrically studied. These numerical studies demonstrate that discontinuous nonlinear bistable devices have a significantly broadened frequency range that elicits the large amplitude snap through behavior. It is also seen that interwell motion is achievable at significantly reduced excitation amplitudes through these discontinuous structural elements.

A key issue in health monitoring of smart structures is the estimation of modal parameters such as natural frequencies and damping ratios from acquired dynamic signals. In this article, a new methodology is presented for calculating the natural frequencies (NF) and damping ratios (DR) of large civil infrastructure from acquired dynamic signals using a multiple signal classification (MUSIC) algorithm, the empirical wavelet transform (EWT), and the Hilbert transform. The effectiveness of the proposed method is validated by means of three examples: a benchmark 3D 4-story steel frame structure, a benchmark problem, subjected to dynamic loading, an 8-story steel frame subjected to white noise input on a shaking table, and a 123-story highrise building structure, Lotte World Tower (LWT), under construction in Seoul, South Korea. The results demonstrate that the new methodology is accurate for estimating the NF and DR of a superhighrise building structure using low-amplitude ambient vibrations data, a complex and challenging task since the measured vibrations signals are noisy and present non-stationary characteristics. The new methodology can deal with noisy signals without degrading its ability to estimate the NF and DR of different one-of-a kind civil structures thus is particularly suitable for health monitoring of large smart structures under dynamic loading.

This study uses ambient vibrations to monitor rock bolting works, the efficacy of which is usually difficult to estimate. The test site is a 760 m 3 unstable limestone column located in the Bourne valley (Vercors, France). The rock column's resonance frequencies ( f X ) were identified, corrected for reversible thermal effects and monitored over time. We observed clear increases in f X up to ~ 17% resulting from the additional stiffness provided by the steel rock bolts. Numerical modeling helped to confirm that the rebar elements were grouted on both sides of the fracture. The major column's resonance features, such as the resonance frequencies and mode shapes, were successfully simulated, including their evolution with bolting. The amount of f X increase depends on the mode considered, likely controlled by bolt location in comparison with the modal shape. This study confirms the potential of ambient vibrations to provide global in-depth information on the stability evolution of rock compartments, with versatile applications for monitoring potential rockfalls or reinforcement works.

Lithospheric V S models are defined in the Campi Flegrei District (southern Italy) through the non-linear inversion of the group velocity dispersion curves of fundamental-mode Rayleigh waves extracted from ambient noise cross-correlations between two receivers, and the regional group and phase velocities of the Italian cellular lithospheric model (1° × 1° cells). Four paths are investigated, of which one (ISCHIA-MIS) across two adjoining cells. The distribution of V S shows a pyroclastic covering with V S increasing from 0.3–0.7 km/s to 2.1 km/s. It rests on a lava or carbonate basement, about 5–6 km thick, with V S increasing from 2.1 km/s to 3.1 km/s at about 2 km of depth and rising to ∼0.6 km towards the island of Procida. A metamorphic layer is detected at an average depth of 7.7 km with V S of 3.8–3.9 km/s, about 5 km thick, overlying a low velocity layer (V S of 3.5 km/s) at about 11–12 km of depth. The V S model along the ISCHIA-MIS path, as average of the models obtained by combining local and regional dispersion data of the two adjoining cells, is well consistent with the other paths. The Moho discontinuity is retrieved at about 23 km of depth with V S of 4.2 km/s.

The village of San Gregorio (SG), eight kilometres away from L'Aquila (central Italy), was severely damaged by the April 6, 2009 L'Aquila earthquake (M W 6.1). A coseismic fracture zone was mapped along SW-dipping fault segments crossing SG, which is situated at the base of a carbonate relief bounded by the Aterno river alluvial plain. An interdisciplinary approach was used to investigate the seismic response of the area based on geological-structural, geophysical and seismic analyses. We integrated our data with available information from the recent microzonation studies. SG is partly built on alluvial fan deposits constituted by cemented gravel, and partly on jointed carbonate bedrock. An extensive survey of noise measurements showed strong and polarized peaks in the horizontal-to-vertical spectral ratios (H/V), both on soft and rock sites in the 2–10 Hz frequency band. Further, we checked the stability with time of H/V ratios at three sites of SG. An analysis on local earthquakes confirmed the results of noise measurements. To understand the influence of rock mass jointing condition on site effects, we performed structural surveys on carbonate bedrock. We also evaluated the propagation velocities at rock sites using seismic active and seismic dilatometer test (SDMT) surveys. Our analysis showed low values of compressional (V P ) and shear wave (V S ) velocities of the outcropping rock, where we also observed strong H/V spectral peak and high-density rock fracturing.

Marine seismic surveying discerns subsurface seafloor geology, indicative of, for example, petroleum deposits, by emitting high-intensity, low-frequency impulsive sounds. Impacts on fish are uncertain. Opportunistic monitoring of acoustic signatures from a seismic survey on the inner continental shelf of North Carolina, USA, revealed noise exceeding 170 dB re 1 μ Pa peak on two temperate reefs federally designated as Essential Fish Habitat 0.7 and 6.5 km from the survey ship path. Videos recorded fish abundance and behavior on a nearby third reef 7.9 km from the seismic track. During seismic surveying, reef-fish abundance declined by 78% during evening hours when fish habitat use was highest on the previous three days without seismic noise. Despite absence of videos documenting fish returns after seismic surveying, the significant reduction in fish occupation of the reef represents disruption to daily pattern. This numerical response confirms that conservation concerns associated with seismic surveying are realistic.

Seismic low-frequency component included more fluid information, which was still a focus in geophysics. Seismic pre-stack data contained more fluid information, but signal to noise ratio (SNR) was low. By comparison, seismic post-stack data had a high SNR, but some fluid information was lost during data processing. Different angel stacks reflected different fluid seismic amplitude, compared with near-angle stacks. Far angle stacks had more low frequency components, which were more benefit for fluid identification. Based on this principle, combined with the pre-stacks and post-stacks seismic data, more fluid information would be included. In this study, a new fluid identification method was proposed. This method combined the post-stack seismic and pre-stack seismic data, it took into consideration high SNR of the post-stack seismic data and the large fluid amplitude differences of the pre-stack different angles. Field testing indicated this method was quite effective in detecting fluids. Keywords: Fluid identification, Seismic low-frequency, Signal to noise ratio, Post-stack seismic data, Pre-stack seismic data

Internal erosion, a major cause of failure of earthen dams and levees, is often difficult to detect at early stages using traditional visual inspection. The passive seismic-interferometry technique could enable the early detection of internal changes taking place within these structures. We test this technique on a portion of the sea levee of Colijnsplaat, Netherlands, which presents signs of concentrated seepage in the form of sandboils. Applying seismic interferometry to ambient noise collected over a 12-hour period, we retrieve surface waves propagating along the levee. We identify the contribution of two dominant ambient seismic noise sources: the traffic on the Zeeland bridge and a nearby wind turbine. Here, the sea-wave action does not constitute a suitable noise source for seismic interferometry. Using the retrieved surface waves, we compute time-lapse variations of the surface-wave group velocities during the 12-hour tidal cycle for different frequency bands, i.e., for different depth ranges. The estimated group-velocity variations correlate with variations in on-site pore-water pressure measurements that respond to tidal loading. We present lateral profiles of these group-velocity variations along a 180-meter section of the levee, at four different depth ranges (0m–40m). On these profiles, we observe some spatially localized relative group-velocity variations of up to 5% that might be related to concentrated seepage.

The Tibetan plateau is formed by the persistent convergence between the Indian and Eurasian plates. The northeastern Tibetan plateau is undergoing young deformation that has been noticed for a long time. We conduct a passive-source seismic profile with 22 stations in NE Tibet in order to investigate the crustal shear-wave velocity structure and its relationship with tectonic processes. In this paper we obtain the Rayleigh-wave phase velocity dispersion data among all station pairs within the period bandwidth of 5–20 s from the method of ambient noise cross-correlations. Phase velocity variations correlate well with surface geological boundaries and tectonic features, for instance, low phase velocity beneath the Songpan–Ganzi block and the Guide basin. We also compute P-wave receiver functions based on the selected teleseismic events with similar ray parameters, and perform the joint inversion of surface wave dispersion data and receiver functions to obtain the 2-D crustal shear-wave velocity structure along the profile. The inversion results show that low shear-wave velocities beneath the Songpan–Ganzi block are widespread in the middle-to-lower crust. In together with high crustal Vp / Vs ratios and high temperature suggested by the P-wave velocities obtained from the active-source seismic study, we suggest that the low velocity zone beneath the Songpan–Ganzi block is probably attributed to partial melting. Across the North Kunlun fault, there is no crustal LVZ found beneath the Kunlun block. This structural difference may have already existed before the collision of the two blocks, or due to limit of the northward extension for the crustal LVZ across the North Kunlun fault.

We present a detailed site effects study at a site (TYF) close to the Thermaikos gulf coast in Thessaloniki, northern Greece. Different types of data recorded by different instruments are analyzed. Empirical amplification is estimated using spectral ratios relative to a reference station (SSR) and horizontal to vertical spectral ratios (HVSR) using earthquake data. In addition, seismic noise records from different arrays were analyzed using HVSR. Our results show that earthquake data SSR fails for our data. The reason is the poor signal to noise ratio of our records. Better results were obtained using HVSR for earthquake data. Seismic noise HVSR were not useful due to the particular soil profile at TYF, with the exception of HVSR of seismic noise recorded in one of our arrays that were able to reflect a significant change in the coast line at our site. Although amplification at site TYF is relatively small, it is large enough to originate a difference of one intensity unit relative to firm ground motion. Amplification at TYF is caused by a deep soil structure (over 350 m in depth) and therefore cannot be captured using measures like Vs30.

Rural houses are recently built using confined masonry walls. The concrete beam and column confining the wall are usually considered to resist lateral loads, such as earthquake load. The Indonesian code requires reinforcement of 12 mm diameter in each corner of the beam and column with 8 mm diameter of stirrups. Such houses are usually termed of non-engineered structures, i.e buildings which the strength is not technically calculated but is established by the communities based on their experiences. This research was aimed to relate the in plane lateral ground acceleration and the resulting lateral displacement on the top of the wall at the first fundamental frequency. As the wall occasionally breaks at certain lateral drift ratio (H/V ratio), therefore, a prediction of the maximum lateral ground acceleration of the wall due to earthquake shake may also be established. Two wall specimens were made of local masonries with dimensions of 3m x 3m and 0.15 m thick. Lateral loads were applied in several stages and ambient vibrations of the two accelerometers, mounted on the base and on the top of the wall, were also recorded in stages. The maximum lateral force prediction, calculated using allowable lateral ground acceleration, was closely approaching the experiment result and numerical calculation.

The H/V technique is used throughout this research to characterize the soil column at different locations of the metropolitan area of Málaga (Southern Spain). This region stands as a good example of a continuously growing zone, mostly developed on soft alluvial sediments, with moderate to low seismicity. The H/V analysis of the noise measurements reveals frequency peak values ranging from 3 to 4 Hz on the NE of the study area, where the basin basement outcrops, to 0.3 Hz in the Guadalhorce River alluvial plain. We correlate the presence of the main H/V peak with the appearance of the basin basement materials in the sedimentary column; whereas secondary peaks obtained in some measurement points may be related to Quaternary and Pliocene sedimentary fill. Shear wave velocity profiles, inverted from the experimental H/V curves, data available from previous boreholes and superficial geology information are all integrated to provide four characteristic 2D cross-sections of the basin. In the ground model described here we distinguish four layers: a shallow layer that is probably linked to the recent Quaternary sediments (Vs from 100 to 500 m/s); an intermediate layer that is related to the presence of late Pliocene materials (Vs from 300 to 1000 m/s); a deep layer associated with early Pliocene materials filling the trough formed by the basin basement (Vs from 700 to 1600 m/s); and finally the basement formation that shows stable velocity at around 2000 m/s. This research has been partially funded by the Research Groups VIGROB-184 (University of Alicante) and by the Spanish Government (Grants CGL2011-30153-C02-02/BTE and CGL2011-25162), the FPU Program at the Ministry of Science and Innovation (AP2008-04686) and the Instituto Alicantino de Cultura Juan Gil-Albert.

In the Mediterranean area, cliff slopes represent widespread high-risk landforms as they are highly frequented touristic places often interested by landslide processes. Malta represents a significant case study as several cliffs located all around the island are involved in instability processes, as evidenced by wide block-size talus distributed all along the coast line. These diffused instabilities are related to the predisponding geological setting of Malta Island, i.e. the over-position of grained limestone on plastic clay deposits, that induces lateral spreading phenomena associated to falls and topples of different-size rock blocks and is responsible for a typical landscape with stable plateau of stiff rocks bordered by unstable cliff slopes. The ruins of GLatin small letter h with strokeajn adid Tower, the first of the thirteen watchtowers built in 1658 by the Gran Master Martin de Redin, stand out in the Selmun area. Currently the safety of this important heritage site, already damaged by an earthquake on October 12th 1856, is threaten by a progressive moving of the landslide process towards the stable plateau area. During autumn 2015, a field-campaign was realized to characterize the jointed rock mass. A detailed engineering-geological survey was carried out to reconstruct the geological setting and to define the mechanical properties of the rock mass. Based on the surveyed joint spatial distribution, 58 single-station noise measurements were deployed to cover both the unstable zone and the stable area. The obtained 1-hour records were analyzed in the frequency domain for associating vibrational evidences to different instability levels, i.e. deriving the presence of already isolated blocks by the local seismic response. The here presented results can be a useful contribute to begin to asses defense strategies for the Selmun Promontory, in the frame of managing the landslide risk in the study area and preserving the local historical heritage. © 2017 The Authors.

By analyzing Rayleigh and Love wave empirical Green's functions extracted from ambient seismic noise and earthquake data, we obtained near surface radial anisotropy structure beneath the hidden part of the Kahurak fault in the Rigan region, in the southeast of Iran. The deduced seismic radial anisotropy within the hidden part of the Kahurak fault can reveal record of shallow crustal deformation caused by the Rigan earthquake (M W 6.5) occurred on 20 December 2010. Significant radial anisotropy with positive magnitude (V SH > V SV ) appears in the shallow subsurface of the upper part of the crust. The magnitude of radial anisotropy varies from predominantly positive (V SH > V SV ) to mostly negative (V SH SV ) values with increasing depth which is correlated with a known sedimentary layer. The sedimentary layer is observed with prominent positive radial anisotropy (V SH > V SV ). The thickness of the sedimentary layer varies between 1 and 3 km from the south to the north beneath the study area with an average radial anisotropy of about 5%. However, cross-section profiles indicate that negative anomaly stretches inside a thick sedimentary layer where the aftershocks occurred. Also, the investigation of cross-section profiles reveals that a dipping angle of the hidden part of Kahurak fault is resolved at approximately 85° using the anisotropy pattern. Moreover, the aftershocks generally occurred in the transitional zones where signs of radial anisotropy anomalies change. Our study indicates that the influence of different resolving powers and path coverage density of Rayleigh and Love waves, which can be artificially interpreted as radial anisotropy, have minor effect on calculated radial anisotropy and they are estimated in the range of − 2% to + 2%.

Analyzing the integrity of a structure and implementing a process to estimate the level of damage in real time increase the safety of people and goods and reduce economic losses associated with the production interruption or operation of the structure. The appearance of damage to a building changes its dynamic response (frequency, damping and/or modal shape) and, therefore, one of the most effective methods for continuous assessment of integrity is based on the use of ambient vibrations. However, if the resonance frequency can be used as indicator of changes, a misinterpretation can be due to the fact that frequency is not only affected by the occurrence of damage, but also by certain operating conditions and especially certain atmospheric conditions. In this study, after analyzing the correlation of the resonance frequency values with temperature for one building, we used the data mining method called "association rule learning" (ARL) to predict the future frequency depending on the measured temperature. We then propose an interpretation strategy of anomalies using the method called "traffic-light".

The aim of this study was to establish a 3D shear-wave velocity model of the transition zone between the Eastern Alps and the Pannonian basin by means of ambient noise tomography. Datasets from permanent networks as well as past and recently deployed temporary networks of broadband seismic stations have been processed. Empirical Green's functions were estimated via cross-correlation of vertical component ambient seismic noise and further processed to obtain Rayleigh-wave group-velocity dispersion curves. They were directly inverted for shear velocities through a wavelet-based sparsity-constrained tomography method avoiding the intermediate step of constructing 2D group velocity maps. A horizontal resolution of 0.2° in the upper crust and 0.3°–0.5° in the lower crust was achieved. Our upper crustal shear velocity model revealed low velocities in the sedimentary depocenters and high velocities below the surrounding mountains. However, at greater depths (24–29 km), high shear velocities beneath the basins suggest crustal thinning accompanied by mantle updoming. An extremely deep low velocity anomaly was mapped beneath the Vienna basin, which we argue is caused by either sediment transfer to the lower crust; ductile deformation suggested by seismic anisotropy; or the presence of fluids.